Technical – Running in the clouds

Oracle Linux in-place upgrade. Good, bad and the cloud. #JoelKallmanDay

Oracle Linux 7 was released in 2014 and the system is close to its sunset. The premier support for the system will be wrapped up by July 2024 and it is time to think about moving forward. All the new systems, as I can see, are using version 8 and some even version 9. So it is time for an upgrade. And when we speak about upgrading we usually have two options – in-place and out-of-place. The in-place upgrade modifies the system on the same box keeping all the users data intact and the second approach is more like a migration when you move all your app stack and data to a new box with a new version of the OS. So, how difficult is the in-place upgrade and when it makes sense?

Sample Go application with database backend

Yes, this is one more sample app as there are probably thousands already on the internet. We have tons of sample apps from different vendors with various types of licenses available on different repositories. Nevertheless sometimes I struggle to find exactly what I need – a simple app with a database backend which can work with Oracle Autonomous databases and optionally with Postgres backend. In my everyday life I primarily use Go as a programming language and I would like to have such an app written using that language. So, eventually I gave up and created my own application with a simple frontend and two (as for now) options for backend databases – Oracle and Postgres.

MongoDB on Oracle Autonomous

Earlier this year Oracle announced support for MongoDB API on the Oracle Autonomous database family. It has been recognized as a huge milestone by Forbes and multiple other analysts, technical and market experts. In my opinion it was logical and fully predicted one more step to the main idea of “Converged Database”. I didn’t coin that term – Oracle was using it for two or three years as of now. The main idea is to create a fully managed database platform supporting the most of APIs and interfaces and put the data together under the Oracle Autonomous Database umbrella. Here I will try to look inside and understand what it is, how it works, what is supported and what is not.

Data Pump Export on Oracle Autonomous

The blog was supposed to be a small how-to but it has grown to a bigger one and hopefully might help to avoid some minor problems while exporting data from an Autonomous Database (ADB) in Oracle Cloud (OCI). It is about exporting data to the Oracle DataPump format to move data to another database or as a logical “backup”.

Oracle documentation provides sufficient information but I find it more and more difficult to navigate considering the number of options and flavours for Oracle databases. There are some new ways and tools around Oracle OCI ATP which can help in some cases. If you want you can jump directly to the end to read the summary.

Blog on Oracle OCI ARM free tier.

This blog was primarily driven by questions from my peers and colleagues who wondered where my blog was hosted and how it was created. It might help to move from a hosting platform to your own website and where to start.

Like most bloggers I started my blog using one of the hosting platforms but soon after found some limitations in choosing appearance, plugins and was a bit annoyed by some commercial banners on my page. After a while I decided to move to my own site. I bought a domain name for myself and created my own environment using the WordPress software on a cloud VM. It didn’t cost me too much but it was not entirely for free. When Oracle introduced some additions to the always free set of resources. I decided to give it a try and move my blog entirely to the OCI free tier.

For those who would like to skip the reading and try, I have a set of Terraform scripts on GitHub. They haven’t been updated lately and use not the latest versions but can be a good place to start.

Anthos Config Connector and Redis security

A short disclaimer. I am writing it in the middle of March 2022 and it is possible that when you read the blog the information published here is not relevant anymore. Cloud products are evolving very fast.

I write the post to share some observations and potential issues you might have with deploying GCP Memorystore for Redis instances through Anthos Config Connector (ACC) controller. If you are not familiar with ACCI, I strongly recommend reading at least a high level overview of the product. In essence this is a Kubernetes addon which allows you to automatically deploy and manage GCP services by applying a manifest file (YAML or Helm chart) to a Kubernetes cluster with the ACC controller. It allows you to use the Kubernetes cluster as a deployment tool for GCP resources in your organization. This is a really interesting approach and might transform your environment in the cloud. But it implies some challenges around security which I am going to discuss in the blog.

Google Cloud SQL Custom Backups

In one of my previous posts I’ve noted that the GCP Cloud SQL for SQL Server doesn’t have point of time recovery as of March 2022. As result the default out of box backups can only provide RPO as 24 hours or more. The exact RPO might vary from day to day since you can only specify a window for backup but not exact time. So far it seems like the only reasonable approach to reduce the RPO is to schedule on-demand backups, and in this post I am going to show how you can do that using a couple of different approaches.

Is Google Cloud SQL Server enterprise ready?

Before starting the post let me clarify that what I am going to describe as the state of readiness of the Google Cloud SQL Server is actual for early February 2022. It is quite possible that some things can be different when you read the post.

For the last several months I was helping some big enterprises to adopt Google Cloud Platform (GCP) and, as part of the implementation, a significant number of SQL Server databases were moving to the GCP Cloud SQL service. But when we started to build the environment in GCP it was clear that the SQL Server option for Cloud SQL is much inferior not only to some other cloud offerings and on-prem installations but also to other databases engines on the same Cloud SQL. In short the SQL Server on GCP Cloud SQL service lacked some essential features. Here I will try to explain why I think the SQL Server in GCP is not mature enough for enterprise.

Docker image to work with GKE in GCP

Lately I work primarily with Google Public Cloud (GCP) and in particular with Kubernetes services (GKE). As result my daily routine command line tools are gcloud, kubectl, nomos and other. And when the GCP cloud shell is really amazing environment which doesn’t require any effort to fire up, sometimes it is not possible to use. When it comes to work from your own laptop you have different options. You can install the tools like Google Cloud SDK following several simple steps from the Google website or you can prepare a docker image and run it in a container. I personally prefer the second way. In such case I can periodically update entire environment without too much effort and easily can span a new environment on any laptop fairly quickly. Here I am sharing what I personally use for my day-to-day activity.

Terraform modules simplified.

Terraform is probably already the de-facto standard for cloud deployment. I use it on a daily basis deploying and destroying my tests and demo setups in my Oracle cloud tenancy. Sometimes the deployment environment for a demo has too many files or some files inside are really big and hard to read due to the number of different resources and parameters included there. How can we make our configuration more usable? Let’s try Terraform modules and demonstrate how they work.
For our tests we are going to use terraform v1.0.3 and Oracle Cloud Infrastructure (OCI). You will need a working OCI and on your machine with terraform defined environment variables. The full list of required environment variables will be provided in the README file in the GitHub repository.
Let’s say we have a simple demo or test configuration with a dedicated network, internet gateway and a VM. And we want to assign multiple security rules using security lists and maybe one or two security groups. We can include all those rules to the configuration file for the network but maybe there is a better way. What if we want to reuse the similar set of the security rules and security groups not only to that deployment but share with some other stacks? We can try to use Terraform modules.

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